Background Below-normal availability of water for a considerable period of time induces occurrence of drought. This paper investigates the Spatio-temporal characteristics of meteorological drought under changing climate. The climate change was analyzed using delta based statistical downscaling approach of RCP 4.5 and RCP 8.5 in R software packages. The meteorological drought was assessed using the Reconnaissance Drought Index (RDI). Results The result of climate change projections showed that the average annual minimum temperature will be increased by about 0.8–2.9 °C. The mean annual maximum temperature will be also increased by 0.9–3.75 °C. The rainfall projection generally showed an increasing trend, it exhibited an average annual increase of 3.5–13.4 % over the study area. The projected drought events reached its maximum severity indicated extreme drought in the years 2043, 2044, 2073, and 2074. The RDI value shows drought will occurred after 1–6 and 2–7 years under RCP 4.5 and RCP 8.5 emission scenarios respectively over the study area. Almost more than 72 % of the current and future spatial coverage of drought in the study area will be affected by extreme drought, 22.3 % severely and 5.57 % also moderate drought. Conclusions Therefore, the study helps to provide useful information for policy decision makers to implement different adaptation and mitigation measures of drought in the region.
Ethiopia will be more vulnerable to climate change. Because of the less flexibility to adjust the economic structure and being largely dependent on agriculture, the impact of climate change has far reaching implication in Ethiopia. Simulation models of watershed hydrology and water quality are extensively used for water resources planning and management. The study aims to Simulate Hydro Climatological impacts caused by Climate Change: the case of Hare Watershed, Southern Rift Valley of Ethiopia. In the study the daily data values of rainfall and discharge for the current period of 1980-2006 were used. Historical Representative Concentration Pathway (RCPs) data of precipitation and temperature were used to extract raw climate variables. The raw RCPs data were corrected using a bias correction method. The downscaled climate data such as, RCP4.5 and RCP8.5 scenarios was used for the future period assessment. Soil water assessment tool (SWAT) models were used to Simulate Hydro Climatological impacts caused by Climate Change. Calibration and validation of the model output were performed by comparing 8.0, and 13.9% at 2020s, 2050s, and 2080s, respectively, from the baseline period for RCP4.5 scenario, whereas for RCP8.5 scenario, it will be expected to increase by 7.3, 13.4, and 15.4% for 2020s, 2040s, and 2080s, respectively. The model simulations considered only future climate change scenarios assuming all spatial data constant. But change in land use scenarios other climate variables will also contribute some impacts on future stream flow.
Hydrological extreme events such as floods and drought are common in Ethiopia which eventually causes environmental hazards. Kulfo River is one of Southern Ethiopian Rift Valley Basin that has experienced flooding for years. Therefore, this study aimed characteristics of hydrological extremes in the Kulfo River, which is important for effective drought and flood monitoring and early warning systems. The hydrological drought was assessed using the streamflow drought index (SDI). Flood frequency distribution (FFD) software package was deployed to determine the flood frequency curve of the Kulfo River. The goodness-of-fit test results showed that the Generalized Extreme Values (GEV) distribution was found the best-fit probability distribution model in the Kulfo River, while the results of SDI values showed that extreme drought events were observed in 1991, 1992, and 2014 with magnitudes ranging from − 2.04 to − 2.7, − 2.0 to − 2.3, and − 2.10 to − 2.24, respectively, which cause reduction of lake level, lowing of groundwater level, and decreased the amount of river flow. SDI value indicated 6-year drought duration has occurred with the relative frequency of 20% in the 3-and 6-month timescales. The flood frequency results show the lowest probability of having flood magnitude has affected the river morphology. The study provides valuable information for policy and decision makers to implement different adaptation and mitigation measures for extreme hydrological events in the Kulfo River.
Meteorological drought is a climate-related natural disaster. It indicates a shortage of precipitation over a long period, usually for a season or a year. This study was initiated to analyze meteorological drought using copula theory. Long-year (1982Long-year ( -2020 rainfall and soil moisture data were used to analyze standardized precipitation index (SPI) and standardized soil moisture index (SSI), respectively. The best-t copula family was selected to construct the joint probability distribution (JPD) of SPI and SSI. Multivariate standardized drought index (MSDI) at 3-, 6-, and 12-month timescales were analyzed using the MSDI toolbox. The non-parametric Mann-Kendall (M-K) statistical test was used for trend detection. The result shows the newly developed MSDI captured all extreme drought events with the highest severity (-3.21) that occurred during the observation period compared to SPI and SSI. MSDI shows the famine caused by the drought of 1984 and 1985 remains well known to the world, with the drought duration and severity of 10 months and 18.7 years, respectively and its joint return period was 33.0 years. The result of the M-K and Sen's Slope estimator statistical tests shows a positive trend for all drought timescales in the basin. The extreme drought captured by the MSDI most frequently occurred in the basin. This implicated that meteorological drought analysis using multiple indices is better than a single index. The results of this study will help devise drought adaptation and mitigation strategies in the basin and beyond.
scite is a Brooklyn-based organization that helps researchers better discover and understand research articles through Smart Citations–citations that display the context of the citation and describe whether the article provides supporting or contrasting evidence. scite is used by students and researchers from around the world and is funded in part by the National Science Foundation and the National Institute on Drug Abuse of the National Institutes of Health.
hi@scite.ai
10624 S. Eastern Ave., Ste. A-614
Henderson, NV 89052, USA
Copyright © 2024 scite LLC. All rights reserved.
Made with 💙 for researchers
Part of the Research Solutions Family.